View in EDS

Harnessing the power of artificial intelligence in pharmaceuticals: Current trends and future prospects.

Saved in:
Bibliographic Details
Title: Harnessing the power of artificial intelligence in pharmaceuticals: Current trends and future prospects.
Authors: Aritra, Saha, Shikha, Chauhan Baghel, Indu, Singh
Source: Intelligent Pharmacy; Jun2025, Vol. 3 Issue 3, p181-192, 12p
Subject Terms: NATURAL language processing, DRUG discovery, ARTIFICIAL intelligence, MACHINE learning, VIRTUAL high-throughput screening (Drug development)
Abstract: Introduction of artificial intelligence (AI) technology in the field of pharmaceutical industry has been driven to discovery and development of drugs, also personalized medicine. In this article The review investigates systematic trends facing AI-powered transformation. AI has improved efficiency by reducing the drug development time, costs and success rates due to machine learning (ML), deep learning (DL) and natural language processing (NLP). The literature search was conducted systematically, using core scientific databases to source data-mining research studies on predictive modelling, virtual screening, and automation in AI applications. Findings here underscore the critical role that AI plays in precision medicine, as well as process optimization in manufacture, but ethical issues and privacy of data and regulations add significantly to hurdles. The study confirms that AI presents unique opportunities for developing personalized healthcare and answering global health challenges, nonetheless its adoption involves overcoming ethical and regulatory issues beautiful collaboration and agreeing to industry wide standards. The next-generation products bring hope for low-cost, patient-centric solutions indicating pharmaceutical landscape phases of the paradigm. [ABSTRACT FROM AUTHOR]
Copyright of Intelligent Pharmacy is the property of KeAi Communications Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Description
Abstract:Introduction of artificial intelligence (AI) technology in the field of pharmaceutical industry has been driven to discovery and development of drugs, also personalized medicine. In this article The review investigates systematic trends facing AI-powered transformation. AI has improved efficiency by reducing the drug development time, costs and success rates due to machine learning (ML), deep learning (DL) and natural language processing (NLP). The literature search was conducted systematically, using core scientific databases to source data-mining research studies on predictive modelling, virtual screening, and automation in AI applications. Findings here underscore the critical role that AI plays in precision medicine, as well as process optimization in manufacture, but ethical issues and privacy of data and regulations add significantly to hurdles. The study confirms that AI presents unique opportunities for developing personalized healthcare and answering global health challenges, nonetheless its adoption involves overcoming ethical and regulatory issues beautiful collaboration and agreeing to industry wide standards. The next-generation products bring hope for low-cost, patient-centric solutions indicating pharmaceutical landscape phases of the paradigm. [ABSTRACT FROM AUTHOR]
ISSN:2949866X
DOI:10.1016/j.ipha.2024.12.001